"The Science of Algorithmic Trading and Portfolio Management,"
with its emphasis on algorithmic trading processes and current
trading models, sits apart from others of its kind. Robert Kissell,
the first author to discuss algorithmic trading across the various
asset classes, provides key insights into ways to develop, test,
and build trading algorithms. Readers learn how to evaluate market
impact models and assess performance across algorithms, traders,
and brokers, and acquire the knowledge to implement electronic
trading systems.
This valuable book summarizes market structure, the formation of
prices, and how different participants interact with one another,
including bluffing, speculating, and gambling. Readers learn the
underlying details and mathematics of customized trading
algorithms, as well as advanced modeling techniques to improve
profitability through algorithmic trading and appropriate risk
management techniques. Portfolio management topics, including quant
factors and black box models, are discussed, and an accompanying
website includes examples, data sets supplementing exercises in the
book, and large projects.
Prepares readers to evaluate market impact models and assess
performance across algorithms, traders, and brokers.
Helps readers design systems to manage algorithmic risk and dark
pool uncertainty.Summarizes an algorithmic decision making
framework to ensure consistency between investment objectives and
trading objectives.
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